What Gets Measured Gets Done: The Importance Of Tracking Business Metrics

Last Updated: January 8, 2024 | by Paul Harstrom

Some companies claim that certain strategies or approaches to increase revenue do not work for them. It is often because there is an internal issue within the company itself. The resolution lies in addressing these internal issues through Tracking business metrics or KPIs

Therefore, the importance of business metrics or measurable indicators cannot be overstated, as they are a significant tool for diagnosing and rectifying internal challenges.

This article will explain the importance of tracking business metrics to improve a company’s revenue-generation strategies.

What Gets Measured Gets Done

Charles Schwab, the visionary founder of Bethlehem Steel, once undertook an influential visit to one of his struggling steel mills. He inquired about the day’s production and learned they had completed six “heats.” Schwab, with a keen understanding of motivation, seized the opportunity. 

Using a piece of chalk, he inscribed a prominent six on the factory floor and left without saying a word. The impact was profound. Upon spotting the marked six, the next shift comprehended its significance and set out to exceed it. The subsequent shifts grasped this competitive spirit, erasing the prior number and striving for even greater accomplishments.

The essence lies in the profound impact of measuring and displaying performance metrics. It triggered a cascade of motivation, with each shift aiming higher. 

This story vividly encapsulates the powerful concept of “what gets measured gets done.” The act of measuring and displaying a performance metric became a catalyst for continuous improvement.

“It’s not enough to have a good idea in business; you must measure, refine, and adapt to succeed.”

Paul Harstrom

Knowing something is essential, especially for the leadership team, makes people pay attention. This means that when you measure and track specific metrics, it tends to lead to better results.

Business Metrics And Their Types

Business metrics are essentially standardized numerical measurements that companies use to track, assess, and analyze various aspects of their performance or operations. 

What Gets Measured Gets Done

These metrics provide important insights and help decision-makers make informed choices based on concrete data. The choice of which specific metrics to track depends on the company’s unique characteristics and the areas it wants to focus on for evaluation.

The three most commonly used business metrics types include:
  • Outcomes Metrics
  • Performance Metrics
  • Key Performance Indicators KPIs

Outcome metrics act as a final evaluation, like a report card, summarizing the success of major projects. 

Performance metrics are real-time check-ins, like monitoring runners during a marathon offering ongoing insights into current processes. 

Key Performance Indicators (KPIs) serve as vital health indicators for a business, such as an e-commerce platform tracking its conversion rate, acquisition cost, and cart completion rate, providing a focused view of overall success and health.

Importance Of Tracking Business Metrics

Tracking business metrics is essential due to several advantages it offers. Some of these are given as:

  • When people, especially the leadership team, understand the importance of specific metrics, it helps the company focus on what matters.
  • Keeping track of critical metrics helps prevent issues and saves time by addressing problems early on.
  • Metrics provide a “pulse” of the company’s current state, allowing for predictions and proactive management to avoid potential issues.
  • Metrics provide personal satisfaction and a sense of accomplishment to drive better performance.
  • Knowing performance is measured creates healthy competition and increases dedication.
  • Performance measurement makes people responsible for their work, pushing them to meet or exceed expectations.
  • Acknowledging hard work motivates individuals to keep putting in the effort.

What does it mean to bring our whole selves to work each day? How can we more thoughtfully invest in the growth of the people around us? When the stakes are high, and the company needs us to perform, how do we lead under pressure

To answer these questions, click here and visit the WiLD Toolkit offered by LEAD Diligently. It is a Whole + Intentional Leader Development System to measure different leadership parameters and improve results wherever needed.

Building A Prediction Muscle Through Analyzing Business Metrics:

Managing metrics is similar to building a “prediction muscle”. It refers to the ability to anticipate and predict future outcomes or issues based on current and historical data analysis.

Just as muscle strengthens with regular exercise, the act of consistently managing and analyzing metrics helps the team become more adept at:

  • Predicting trends
  • Identifying potential problems early
  • Making informed decisions

Thus, tracking business metrics creates a culture of accountability within a high-trust and healthy environment. The goal is accurate, timely, and relevant information to inform strategic decision-making.

Measures vs. Metrics:

Measures are numerical representations of specific attributes, such as sales, customer numbers, or inventory levels. They express physical quantities without providing context and also having specified units. 

Measures serve as raw data points, offering a snapshot of a particular aspect of a business at a specific point in time. For instance, the number of employees or website traffic is measured. These individual data points are fundamental as they form the basis for more comprehensive analysis.

Metrics, on the other hand, go beyond individual measures. They are expressions of the relationship between two or more measures, providing context and insights into how they interact. 

Metrics involve calculations, often using fractions, ratios, or percentages, to derive meaningful conclusions. Examples of metrics include customer retention rate, profit margin, and return on investment. 

Metrics enable businesses to understand the implications of their measures, offering a more comprehensive view of performance and aiding in strategic decision-making.

While measures provide specific data points, metrics bring depth and meaning to these data points by establishing connections and relationships between them.

For example, the number of new customers gained, and the total marketing expenses represent specific data points or measures. However, when these measures are used together to calculate the Customer Acquisition Cost (CAC), it becomes a metric. 

The CAC metric offers a meaningful relationship between the cost incurred and the effectiveness of the customer acquisition strategy. It helps us understand how much it costs to get each new customer, showing if our marketing strategy is efficient and profitable.

How do you collect and report data for each measurable business Metric?

Collecting and reporting data for each metric or measurable metric can vary depending on the nature of the metric, the organization’s workflow, and the guiding principle that what is measured improves. Here are some general steps and considerations:

The process of identifying where relevant data resides is a foundational step in effective data management. This involves a comprehensive analysis of various potential data sources within the organization. For instance:

  • Financial Statements: These are crucial for metrics related to financial performance, such as revenue, expenses, and profitability.
  • Customer Databases: Essential for customer-related metrics, including purchasing patterns, customer satisfaction, and demographic data.
  • Project Management Tools: These provide data on project timelines, resource allocation, and progress metrics.
  • Other Systems: This includes a range of systems such as inventory management, human resources, and marketing analytics tools.

A thorough inventory of these sources helps in creating a map of available data, guiding the data collection process effectively.

Deciding on the methods for data collection involves striking a balance between efficiency and accuracy. Methods include:

  • Manual Data Entry: Suitable for data that cannot be easily automated, such as qualitative feedback or ad-hoc reports. It’s essential to minimize human error in manual entry through training and double-checking procedures.
  • Automated Data Extraction from Software Tools: Ideal for large volumes of data or data that is regularly updated. Automation tools can pull data from various systems, ensuring timely and accurate data collection.
  • Combination of Both: Often, a hybrid approach is most effective, using automation for bulk data and manual methods for specialized or non-standard data.

The choice of method should be guided by the nature of the data, the frequency of updates, and the resources available.

Assign responsibility for data collection to specific individuals or teams within the organization. Clearly define who is accountable for ensuring accurate and timely data is available.

Leadership’s Role in Delegation and Oversight

Leadership plays a critical role in assigning and overseeing data collection responsibilities. This includes:

  • Delegating Responsibilities: Assigning data collection tasks to specific individuals or teams based on their expertise and the nature of the data. For example, financial data might be best handled by the finance team, while customer data might be managed by the sales and marketing teams.
  • Defining Accountability: Clearly establishing who is responsible for the accuracy and timeliness of each data set. This involves setting clear expectations and benchmarks for data collection performance.
  • Monitoring and Support: Leaders must actively monitor the data collection process and provide support where needed. This could involve regular check-ins, providing additional resources, or addressing challenges faced by teams.
  • Training and Development: Ensuring that individuals and teams have the necessary skills and knowledge to collect data effectively. This may involve formal training sessions, workshops, or on-the-job training.

Leadership involvement in these aspects ensures that data collection is not just an operational task but a strategic priority, aligned with the organization’s broader goals.

By actively participating in this process, leaders can drive a culture of data-driven decision-making, enhance the accuracy and reliability of data collection, and ultimately contribute to the organization’s success.

Leadership Role in Key Performance Indicators

Determine how often data needs to be collected. Data collection is likely to be a weekly activity for a weekly leadership team scorecard. Some metrics might require more frequent or less frequent updates.

For instance, financial metrics might be gathered monthly to align with financial reporting cycles, whereas customer satisfaction metrics could be assessed after every customer interaction.

High-volume data, like website traffic, may require daily or even real-time monitoring to respond quickly to trends. It’s essential to balance the need for up-to-date information with the resources required for data collection.

Over-collecting data can be as detrimental as under-collecting, leading to information overload without providing additional value.

The advent of advanced technologies offers immense potential for automating data collection. Automation tools can significantly reduce manual labor, minimize errors, and enable real-time data analysis.

For example, Customer Relationship Management (CRM) systems can automatically track sales and customer interactions, while Enterprise Resource Planning (ERP) systems can streamline data collection across various business operations.

Utilizing IoT devices for real-time monitoring of manufacturing processes or supply chain operations can provide immediate insights into performance metrics.

The key is to identify repetitive, time-consuming tasks that can be automated, thus freeing up valuable human resources for more strategic activities.

Consistency in reporting is crucial for accurate interpretation and comparison of data over time. Developing standardized templates and reports ensures that all stakeholders are viewing and interpreting the same information.

Consistent formats also aid in identifying trends and anomalies more quickly. This could mean using a uniform set of visualizations, like graphs and charts, or a consistent layout in reporting tools.

For example, dashboards should have a logical flow and grouping of information, making it easy for users to find what they need and draw accurate conclusions.

Tracking Business Metrics – Key Performance Indicators

Implement processes for verifying and validating the accuracy of collected data. This could involve regular audits, cross-referencing with other sources, or implementing checks and balances.

Integrating data collection processes with existing project management and analytics tools is a strategic move that can streamline workflows and enhance accuracy. Such integration ensures that data flows seamlessly between systems, reducing the need for manual data entry and the associated risk of errors.

For instance, integrating a Customer Relationship Management (CRM) system with marketing analytics tools can provide a comprehensive view of customer engagement and campaign performance.

Similarly, connecting HR systems with productivity tracking tools can offer insights into workforce efficiency and resource allocation. To achieve this, it’s important to choose tools that offer compatibility and support integration through APIs or built-in connectors.

A successful integration leads to a more unified and efficient approach to data management, enabling better decision-making and resource optimization.

Effective communication and training are vital for the successful implementation of any data collection process.

It’s crucial to clearly articulate the purpose, methods, and expected outcomes of data collection to all relevant stakeholders. This includes not only the data collection team but also those who will be using the data.

Training sessions should be tailored to different user groups, focusing on the aspects most relevant to their role. For example, training for data analysts might focus on data interpretation and analysis, while training for sales teams might emphasize data entry and reporting procedures.

Regular workshops, webinars, and written guides can facilitate ongoing learning and adaptation. Effective communication and training ensure that team members are well-equipped to handle new tools and processes, leading to more accurate and efficient data collection.

Documenting the data collection process is essential for maintaining consistency and continuity. This documentation serves as a valuable resource for training new staff and for reference when reviewing or modifying the process.

It can also help in troubleshooting issues or discrepancies in the data. Keeping a comprehensive and up-to-date record of the data collection process safeguards the organization against the loss of critical knowledge and facilitates smoother transitions when changes occur.

Establishing a feedback loop is crucial for the continuous improvement of the data collection process. Encourage team members to regularly provide feedback about the process, including any challenges they face or suggestions for improvement.

This feedback should be actively solicited and reviewed on a regular basis. For example, regular meetings or surveys can be used to gather feedback from different departments. Analyzing this feedback can reveal opportunities for refining the process, improving tools, or enhancing training.

A well-structured feedback loop not only leads to a more efficient data collection process but also fosters a culture of collaboration and continuous learning within the organization.

Ensuring the security and privacy of data in collection and reporting processes is paramount, especially when handling sensitive information.

This involves adhering to legal standards like the General Data Protection Regulation (GDPR) and local data protection laws. It is essential to implement robust security measures such as encryption, access controls, and secure data storage.

Regular security audits and vulnerability assessments can help identify and mitigate potential risks. Privacy concerns should be addressed by anonymizing data where possible and ensuring that data collection is transparent and consensual.

Clear policies on data retention and disposal should be established to maintain data integrity and trust. This focus on security and privacy not only safeguards the organization against data breaches and legal repercussions but also builds trust with clients, customers, and stakeholders.

Leadership Responsibility in Data Management

Leadership plays a crucial role in establishing and upholding data security and privacy standards. It is the responsibility of organizational leaders to:

  1. Set the Tone: Leaders should advocate for the importance of data security and privacy, setting a clear expectation for adherence to policies and regulations.
  2. Resource Allocation: Ensure that adequate resources are allocated for implementing and maintaining data security measures. This includes investing in technology, training, and personnel dedicated to data security.
  3. Policy Development and Enforcement: Leaders should be involved in developing comprehensive data security policies and ensuring their strict enforcement. This includes defining roles and responsibilities for data handling and establishing protocols for breach response.
  4. Continuous Education: Keep abreast of evolving data protection regulations and technological advancements. Encourage continuous learning and adaptation among team members through regular training and updates.
  5. Cultivating a Security Culture: Foster a culture where data security and privacy are ingrained values. Encourage employees to be vigilant and proactive in identifying and reporting potential security threats.
  6. Transparent Communication: Communicate openly with stakeholders about data security policies and practices. Transparency in handling data reassures all parties of the organization’s commitment to data protection.

By actively engaging in these responsibilities, leaders not only ensure compliance with data security and privacy standards but also demonstrate a commitment to ethical and responsible data management.

This leadership approach is crucial in establishing a trustworthy and secure data environment, critical for the long-term success and reputation of the organization.

Final Thoughts On The Importance Of Tracking Business Metrics:

Tracking business metrics is akin to spotlighting key aspects of a company’s performance. It is not just about keeping score; it is a powerful motivational tool. 

When employees see tangible measurements, like the number of “heats” produced, displayed prominently in the Charles Schwab case study, it creates a shared goal. It sparks a friendly competition to outperform previous results. 

Fueled by measurable benchmarks, this continuous improvement mindset ensures that everyone is aligned toward achieving better outcomes. Hence, Metrics assess performance and, more importantly, drive a culture of excellence and progress within the organization.

Do you agree with the statement “what gets measured gets done“? Leave your thoughts in the comment section below!


Can metrics enhance customer satisfaction?

By tracking customer-centric metrics, businesses can identify and address pain points, leading to improved products, services, and overall customer satisfaction.

How do metrics contribute to a culture of accountability?

Metrics hold teams accountable by providing clear performance indicators, assigning responsibility, and encouraging a results-driven culture.

How can tracking business metrics prevent potential issues?

Proactive metric tracking helps identify potential issues early, allowing businesses to implement corrective measures and prevent larger problems.

How do metrics support data-driven decision-making?

Metrics provide reliable data for decision-making, reducing reliance on gut feelings and ensuring that strategic choices are backed by concrete evidence.

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